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Sunday, 19 June 2016

Responsible IT Innovation: How to digitally upgrade our society?

by Dirk Helbing (ETH Zurich/Delft
University of Technology) and Jeroen van den Hoven (Delft University of
Technology)

Why is the world
confronted with so many problems, even though we have more data and better
technology than ever? We are not using it rightly.

When Chris Anderson postulated "the
end of theory" in 2008, there was no public outcry. While the new field of
Big Data analytics spread, altogether it seems that scientists did not pay much
attention to the claim that "the data deluge makes the scientific method
obsolete".[1]
This was a big mistake - not only because it weakened the role of science, but
also because of the implications for society at large.

In the meantime, IT companies and
governments around the world have made huge investments in infrastructures and
machine learning tools to store and mine Big Data. There are entirely new approaches
such as predictive policing, "big nudging"[2]
(the large-scale manipulation of individual emotions, opinions, decisions and behaviors[3]
using knowledge from behavioral economics and massive amounts of personal
data), and citizen scores[4]
(rewarding and punishing citizens for specific behaviors and those of their
friends). Even the idea of predictive sentencing (based on the likelihood of future
offenses) is spreading.[5]
This questions human rights, the separation of powers, democracy and justice - achievements
of hundreds of years of human cultural, political and institutional history,
lessons learnt from many conflicts and wars.

It is time to make up our minds and respond
to the novel, data-driven reality with a constructive operational framework
that enables sustainable new modes of political thinking. Digital technologies
and data science are now used to shape our societies, to constitute the very
fabric of our sociality, often circumventing science and democratic decision-making.[6] Data-driven updates of historical ways of running societies are now
in the making, for example, fascism 2.0 (a big brother and brave new world
society), communism 2.0 (distributing rights and resources based on a
paternalistic "benevolent dictator" approach),
feudalism 2.0 (based
on a few monopolies and a new kind of caste system), and
capitalism 2.0 (discussed below). Moreover, cybernetic concepts of society, which
use automated feedback loops, have spread from Chile to Singapore to other
countries.[7] Google is aiming to build the operating system of the digital
society,[8] and IBM's Watson is proposed for US president.[9] Some experts even suggest, Artificial Intelligence will solve the
world's problems, once machine intelligence surpasses human intelligence.[10] Is this a reasonable expectation?

We must question such overly optimistic claims and projections. Even strong supporters of new technologies such as Big Data and Artificial Intelligence should better acknowledge their limitations and side effects. One would think that, before one tries to turn the world into a "data-driven paradise", one would demonstrate the feasibility of this idea and the superiority of the new approach. However, none of the leading IT nations has succeeded in contributing to the top 10 most livable cities on our planet. In addition, the world is in pretty bad shape, in spite of the fact there are more data and better technologies than ever. Financial crises, violent conflicts, mass migration around the planet, increasing cyber threats, dangerous global warming and emerging shortages of resources are just a few examples of problems, for which data-driven solutions have not been found. We also have not managed to overcome the last financial, economic, and public spending crisis, while the next one seems to be looming already.

The fact that we are far from solving these
problems is actually not by chance.

First, conventional Big Data analytics must
be improved in various aspects. So far, there is a lack of quantitative indicators
to judge the quality of Big Data analyses. The bigger a data set the more
spurious correlations and meaningless patterns occur. For instance, most
patterns of stars one sees in the sky do not have scientific relevance. Given such
"over-fitting" problems, how significant are Big Data results from a
statistical point of view? How much are they biased by the data providers and
those who build and choose the algorithms? To what extent do information
systems help people to take well-informed, conscious and responsible decisions,
and to what extent do they opinionate or manipulate them?

Second, how robust are the results of Big
Data analyses, given the issue of parameter sensitivity? For example, how much do
classification results and error rates depend on the classification method and model
parameters applied? In fact, for every terrorist there are hundreds of people
on the lists of terror suspects, who will never commit a serious crime. More generally,
how often do Big Data analyses discriminate people, and how to protect or
compensate them?[11] For instance, what if health insurance rates would depend on the
food that people eat: would it be fair to charge women and men, Jews,
Christians and Muslims different amounts (on average)?

Third, going one step further, how much
trust, how much solidarity and other social capital is destroyed or exploited by
today's data-driven business models?11 This is important to know if
we want to avoid the risk that public interests are undermined and public
values corroded. For example, there is increasing awareness that "big nudging"
weakens critical thinking and resistance to propaganda, social cohesion, informational
self-determination, and the self-control of our lives.2 Thus, how
well are the implications of Big Data algorithms compatible with democracy,
freedom, fairness, human rights, and the separation of powers? Scientists
should start to measure these things. One urgently needs ways to assess the
quality of data and algorithms - to be precise: various kinds of qualities. And
one needs different standardized ways to look at data: digital filters
providing pluralistic perspectives.

A system that is oriented at a single
indicator (such as gross national product per capita or a citizen score) does
not serve humans well. It is crucial to create tools and institutions, which support
the transparent design of technological systems that are compatible with the moral,
social and cultural values of a society. For example, system designs for
efficiency may look different from designs for sustainability, usability,
flexibility, resilience, fairness, equality, justice, transparency,
accountability, (informational) self-determination, self-organization, democracy,
inclusion, dignity, happiness, well-being, inspiration, creativity, innovation,
safety, security, health, empathy, friendship, solidarity, participation, or
peace. Virtual Reality may now help to make these various perspectives
understandable.

Importantly, Responsible Data Science and
Responsible AI require value pluralism.[12] Therefore, the use of Big Data and AI should be opened up beyond
the circles of big corporations, secret services and the military, as the
openAI initiative demanded as well. The complexity of modern societies requires
the ability to see and judge the world from various perspectives and to bring
them in a suitable balance, otherwise a society becomes dysfunctional sooner or
later. To achieve a high quality of life, one needs pluralistic,
flexible, adaptive, context-dependent and culturally fitting schemes of
governance, which offer diverse opportunities for many different groups of
people. Compared to this, today's data-driven schemes
to govern societies are overly simplistic. While they claim to be
human-centric, the great majority of people has actually no say in how the new
operating system would work and what would be its goals.

However, it is important to understand
that society is not a machine. Automating and running it like a modern
production line is not adequate. For example, it would not be
enough to simulate majority decisions in a computer using digital doubles. This
would mean to turn average behaviors into social norms or standards, which would
constitute something like a majority dictatorship with little protection of
minorities - certainly not a desirable governance approach. The long-term consequences
could be a loss of socio-economic diversity, a decline in the innovation rate,
the loss of economic efficiency, and socio-political instability, potentially
leading to war. To achieve culturally fitting, sustainable and legitimate
results, deliberation processes are crucial. By identifying solutions that are
satisfactory from various perspectives they manage to serve different
functionalities at the same time. Moreover, by combining and integrating
various perspectives, they create innovative solutions that manage to bring
different interests under one roof.[13]
This calls for suitable deliberation platforms enabling democracy 2.0,[14]
which support the emergence of collective intelligence, i.e. of solutions that
are better than any single solution by unleashing the potential of diversity. Civil
society is still an underused resource.

Of course, governments should utilize the possibilities
of data and information technologies. However, it is highly non-trivial what
constitues a responsible and good use. The
statement "code is law" reflects the fact that algorithms
increasingly shape our reality.[15]
While the behavior of people is regulated by hundreds of laws, algorithms are
subject to very few regulations, even though they may have super-human powers.
This is inappropriate and dangerous, as actors without legitimate grounds can increasingly
interfere with the lives of millions of people, often without their knowledge.
Altogether, this does not seem to be helpful. Humans are increasingly losing
control over the information and communication technologies they have created.
For instance, cybercrime costs us 3 trillion dollars annually, and it is
increasing exponentially. Therefore, our judgment is that companies
and institutions are just at the beginning of making good use of Big Data and AI.
The application of these technologies is not yet mature. They lack
participatory opportunities, transparency, and mechanisms to promote fact-based,
responsible, ethical and legitimate use.

While many
countries and companies may have put in place IT infrastructures to control
society with the very best intentions, these imply serious new threats.
Imagine, for example, that political extremists would gain control over today's
powerful IT tools, which enable effective and hard-to notice censorship and
propaganda. It is clear that this could have catastrophic and irreversible consequences.
For such reasons, one must ensure that the use of powerful IT tools will be soon
embedded in a suitable institutional framework. Improvements are urgently needed,
including parliamentary control, scientific use, ethical oversight,
transparency, and compensation of victims. In some democratic countries one can
already see what can happen if one does not take care of these things. A
gradual restriction of democratic principles or even a transition to a totalitarian
state appear to be entirely possible.

In summary, super-intelligent systems will certainly help us to solve a number of difficult problems, but not all. Social capital, culture, security, peace, financial stability, mass innovation, and thriving lives (including jobs for all) seem to be out of scope. To address these issues, there is a need to digitally upgrade our socio-economic system. It is important to understand that the digital transformation of societies takes place in two phases: The first phase is based on Big Data, Artificial Intelligence, and top-down solutions, but it is likely to destroy more jobs than it creates. The second phase will add open and participatory bottom-up structures and create a decentralized information, innovation, production and service ecosystem, using a combination of the Internet of Things, Complexity Science, FinTech (e.g. Bitcoin-inspired block chain technologies), and new kinds of Social Technologies such as personal digital assistants.

As Albert
Einstein said: "One can not solve our problems with the same kind of
thinking that created them." To fix our problems, there is a need for a
new paradigm, otherwise societies will fail. Therefore, we propose to digitally
upgrade capitalism, the so far most successful economic system, which is based
on bottom-up self-organization, entrepreneurial and individual freedom,
competition, high innovation rates, efficiency, flexibility, and resilience. Now,
one needs to add a liberal and democratic framework supporting "(eco-) systems
thinking", co-creation, co-evolution, and collective intelligence.

The Internet of
Things will finally allow us to measure external effects of interactions, to
price such positive and negative externalities, and to trade them in a
multi-dimensional way - a system we propose to call "finance 4.0".
This will create entirely new markets, but first of all, promote resource
efficiency, a circular economy, sharing, and cooperation. In this
multi-dimensional exchange system, additional kinds of "money" can be
created in a bottom-up way. This can generate a living for everyone and public
resources in times, where progressive automation is threatening incomes, taxes,
and consumption, i.e. the basis of our economy. Let us now build the framework
for the digital society to come. There is no time to lose.

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The activities leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 284709 - project 'FuturICT', a Coordination and Support Action in the Information and Communication Technologies activity area